Automatic speech recognition using articulatory features from subject-independent acoustic-to-articulatory inversion
An automatic speech recognition approach is presented which uses articulatory features estimated by a subject-independent acoustic-to-articulatory inversion. The inversion allows estimation of articulatory features from any talker's speech acoustics using only an exemplary subject's articu...
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Published in | The Journal of the Acoustical Society of America Vol. 130; no. 4; pp. EL251 - EL257 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Melville, NY
Acoustical Society of America
01.10.2011
American Institute of Physics |
Subjects | |
Online Access | Get full text |
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Summary: | An automatic speech recognition approach is presented which uses articulatory features estimated by a subject-independent acoustic-to-articulatory inversion. The inversion allows estimation of articulatory features from any talker's speech acoustics using only an exemplary subject's articulatory-to-acoustic map. Results are reported on a broad class phonetic classification experiment on speech from English talkers using data from three distinct English talkers as exemplars for inversion. Results indicate that the inclusion of the articulatory information improves classification accuracy but the improvement is more significant when the speaking style of the exemplar and the talker are matched compared to when they are mismatched. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Author to whom correspondence should be addressed. |
ISSN: | 0001-4966 1520-8524 1520-8524 |
DOI: | 10.1121/1.3634122 |